Applied AI Scientist - Commercial

About the role

The Applied AI Scientist – Commercial builds and deploys machine learning and agentic AI systems that improve pricing, contracting, customer, and portfolio decisions across Amneal’s generics and specialty businesses. This is a hands-on technical role accountable for production systems used daily by Commercial Operations, Pricing & Contracting, Marketing, and Market Access, with business outcomes baselined and validated by Finance. The role sits within the Enterprise AI Transformation function.

Decision Support Systems

• Develop predictive and optimization models with LLM as interface supporting customer bid and tender decisions, including win-probability modeling and price–volume trade-off analysis across the generics portfolio.
• Build revenue and volume forecasting models at NDC and brand level accounting for competitive entrants, loss of exclusivity, price erosion curves, and customer concentration.
• Analyze gross-to-net performance, chargeback, and rebate data to identify and quantify margin leakage, and implement recurring detection rather than one‑time analysis.
• Model customer and channel profitability across wholesalers, GPOs, retail, and specialty accounts to inform contracting strategy and account prioritization.

Business Impact and Governance

• Instrument deployed models with monitoring for drift, data quality, and business KPI degradation, and own remediation.
• Establish benefit baselines with business owners, partner with Finance to validate realized impact, and document methodology to a standard supporting internal audit and SOX review where financially material.
• Present findings, recommendations, and model limitations to Commercial leadership.

Growth & Portfolio Insights

• Build analytics supporting specialty product launches, including patient and prescriber dynamics, payer coverage and access barriers, and field targeting.
• Develop portfolio and business development models assessing new product opportunity: market size, expected entrant count, erosion trajectory, and risk‑adjusted return.

AI Solution Development

• Build LLM-based and agentic applications for commercial workflows, including contract, tender, and market intelligence document extraction, supported by formal evaluation sets and regression testing.

Education

• Bachelor’s degree (BA/BS) in Computer Science, Statistics, Economics, Operations Research, or related quantitative field (with equivalent demonstrated experience) – Required
• Master’s degree (MS/MA) in Computer Science, Statistics, Economics, Operations Research, or related quantitative field – Preferred
• Ph.D. in Computer Science, Statistics, Economics, Operations Research, or related quantitative field – Preferred

Experience

• 5+ years developing and deploying machine learning models in a production environment
• 5+ years advanced proficiency with Python and SQL, including experience with PySpark or comparable distributed processing
• 5+ years demonstrated application of forecasting, pricing, or econometric methods to commercial problems
• 5+ years pharmaceutical or life sciences commercial analytics

Specialized Knowledge

• Working knowledge of agentic LLM application patterns including retrieval-augmented generation, structured extraction, and evaluation methodology – Required
• Track record of working directly with business stakeholders to define problems, agree success measures, and drive adoption – Required
• Generics market dynamics: gross-to-net accounting, chargebacks, rebates, GPO and wholesaler contracting, price erosion modeling – Preferred
• Specialty and branded commercial analytics: payer and market access data, prescriber-level targeting, patient services data – Preferred
• Third-party pharmaceutical data assets – IQVIA, Symphony, or equivalent – Preferred
• Databricks (Unity Catalog, Delta Lake, MLflow) and cloud ML platforms such as Amazon Bedrock or SageMaker – Preferred
• Causal inference methods for observational data – Preferred

Pay

The salary range for this position is $190,000 – $225,000 per year. In addition, Amneal offers a short-term incentive opportunity, such as a bonus or performance-based award within the first 12 months. Individual compensation will ultimately be determined based on qualifications, experience, geographic location, and other relevant factors.